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   "source": [
    "![QuantConnect Logo](https://cdn.quantconnect.com/web/i/qc_notebook_logo_rev0.png)\n",
    "## Welcome to The QuantConnect Research Page\n",
    "#### Refer to this page for documentation https://www.quantconnect.com/docs/research/overview#\n",
    "#### Contribute to this template file https://github.com/QuantConnect/Lean/blob/master/Research/BasicQuantBookTemplate.ipynb"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## QuantBook Basics\n",
    "\n",
    "### Start QuantBook\n",
    "- Add the references and imports\n",
    "- Create a QuantBook instance"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import warnings\n",
    "warnings.filterwarnings(\"ignore\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Load in our startup script, required to set runtime for PythonNet\n",
    "%run ./start.py"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "class CustomDataType(PythonData):\n",
    "\n",
    "    def GetSource(self, config: SubscriptionDataConfig, date: datetime, isLive: bool) -> SubscriptionDataSource:\n",
    "        source = \"https://www.dl.dropboxusercontent.com/s/d83xvd7mm9fzpk0/path_to_my_csv_data.csv?dl=0\"\n",
    "        return SubscriptionDataSource(source, SubscriptionTransportMedium.RemoteFile)\n",
    "\n",
    "    def Reader(self, config: SubscriptionDataConfig, line: str, date: datetime, isLive: bool) -> BaseData:\n",
    "        if not (line.strip()):\n",
    "            return None\n",
    "\n",
    "        data = line.split(',')\n",
    "        obj_data = CustomDataType()\n",
    "        obj_data.Symbol = config.Symbol\n",
    "\n",
    "        try:\n",
    "            obj_data.Time = datetime.strptime(data[0], '%Y-%m-%d %H:%M:%S') + timedelta(hours=20)\n",
    "            obj_data[\"open\"] = float(data[1])\n",
    "            obj_data[\"high\"] = float(data[2])\n",
    "            obj_data[\"low\"] = float(data[3])\n",
    "            obj_data[\"close\"] = float(data[4])\n",
    "            obj_data.Value = obj_data[\"close\"]\n",
    "\n",
    "            # property for asserting the correct data is fetched\n",
    "            obj_data[\"some_property\"] = \"some property value\"\n",
    "        except ValueError:\n",
    "            return None\n",
    "\n",
    "        return obj_data\n",
    "\n",
    "    def __str__ (self):\n",
    "        return f\"Time: {self.Time}, Value: {self.Value}, SomeProperty: {self['some_property']}, Open: {self['open']}, High: {self['high']}, Low: {self['low']}, Close: {self['close']}\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create an instance\n",
    "qb = QuantBook()\n",
    "symbol = qb.AddData(CustomDataType, \"CustomDataType\", Resolution.Hour).Symbol\n",
    "\n",
    "startDate = datetime(2017, 8, 20)\n",
    "endDate = startDate + timedelta(hours=48)\n",
    "history = list(qb.History[CustomDataType](symbol, startDate, endDate, Resolution.Hour))\n",
    "\n",
    "if len(history) == 0:\n",
    "    raise Exception(\"No history data returned\")"
   ]
  }
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